SOTAVerified

Visual Odometry

Visual Odometry is an important area of information fusion in which the central aim is to estimate the pose of a robot using data collected by visual sensors.

Source: Bi-objective Optimization for Robust RGB-D Visual Odometry

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 176–200 of 408 papers

TitleStatusHype
MagicVO: End-to-End Monocular Visual Odometry through Deep Bi-directional Recurrent Convolutional Neural Network—0
Landmark-based Localization using Stereo Vision and Deep Learning in GPS-Denied Battlefield Environment—0
Large Scale Photometric Bundle Adjustment—0
Large-scale visual SLAM for in-the-wild videos—0
Lateral Ego-Vehicle Control without Supervision using Point Clouds—0
Global Pose Estimation with an Attention-based Recurrent Network—0
Learned Camera Gain and Exposure Control for Improved Visual Feature Detection and Matching—0
Learning a Depth Covariance Function—0
Learning-based Image Enhancement for Visual Odometry in Challenging HDR Environments—0
Learning by Inertia: Self-supervised Monocular Visual Odometry for Road Vehicles—0
Discovering Multiple Algorithm Configurations—0
Learning Monocular Visual Odometry through Geometry-Aware Curriculum Learning—0
Learning Monocular Visual Odometry via Self-Supervised Long-Term Modeling—0
Learning monocular visual odometry with dense 3D mapping from dense 3D flow—0
Learning Residual Flow as Dynamic Motion from Stereo Videos—0
Geometry-Constrained Monocular Scale Estimation Using Semantic Segmentation for Dynamic Scenes—0
DeepTIO: A Deep Thermal-Inertial Odometry with Visual Hallucination—0
Geometric Consistency for Self-Supervised End-to-End Visual Odometry—0
Geometric-based Line Segment Tracking for HDR Stereo Sequences—0
Lightweight, Uncertainty-Aware Conformalized Visual Odometry—0
DeepPCO: End-to-End Point Cloud Odometry through Deep Parallel Neural Network—0
LiVisSfM: Accurate and Robust Structure-from-Motion with LiDAR and Visual Cues—0
Local Supports Global: Deep Camera Relocalization with Sequence Enhancement—0
LOF: Structure-Aware Line Tracking based on Optical Flow—0
A Unified Formulation for Visual Odometry—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CIVORelative Position Error Translation [cm]1.36—Unverified